text mining
TEKST MY-ning
tɛkst ˈmaɪnɪŋListen
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the computational extraction of patterns, trends, relationships, and insights from large collections of unstructured or semi-structured text, using techniques from natural language processing, machine learning, and statistical analysis; text mining enables humanists and social scientists to work with corpora at a scale — millions of documents, spanning centuries — that is impossible for any individual reader to process manually; applications in the humanities include identifying stylistic shifts across literary periods, tracking the diffusion of ideas through citation networks, detecting discourse patterns in historical newspapers, and mapping semantic change in language over time; text mining raises methodological questions about the relationship between large-scale quantitative patterns and the fine-grained interpretive readings that have traditionally constituted humanistic scholarship
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